On Constrained Local Model Feature Normalization for Facial Expression Recognition

Real time user independent facial expression recognition is important for virtual agents but challenging. However, since in real time recognition users are not necessarily presenting all the emotions, some proposed methods are not applicable. In this paper, we present a new approach that instead of using the traditional base face normalization on whole face shapes, performs normalization on the point cloud of each landmark. The result shows that our method outperforms the other two when the user input does not contain all six universal emotions.